7885c7f254146ca7a78a6a0b50165e1f12ad529a,dipy/reconst/ivim.py,,two_stage,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,279

Before Change

    flat_x0 = x0.reshape(-1, x0.shape[-1])
    // Flatten for the iteration over voxels:
    bvals_ge_split = gtab.bvals[gtab.bvals > split_b]
    bvecs_ge_split = gtab.bvecs[gtab.bvals > split_b]
    gtab_ge_split = gradient_table(bvals_ge_split, bvecs_ge_split.T)

    tensor_model = TensorModel(gtab_ge_split)
    tenfit = tensor_model.fit(data[..., gtab.bvals > split_b])

After Change

        result = _minimize(flat_data, bvals, flat_x0, ivim_params,
                           bounds, tol, jac, algorithm, gtol, ftol, eps)
    elif routine == "leastsq":
        result = _leastsq(flat_data, bvals, flat_x0, ivim_params)
    ivim_params.shape = data.shape[:-1] + (4,)
    return ivim_params

Instances